With increased service requirements and improved processing demand in a network, the current main solution is that a service is provided by transmitting and processing a service request in the network over the cloud and returning the processed result to a requesting end. However, as media businesses increase, larger data volume and high real-time demand thereof makes it difficult for cloud service to meet a user's requirements, leading to a low degree of satisfaction of the service quality. This is because the main contradiction between the cloud service and media processing in network lies in the following two aspects: one aspect is that the transmission delay of large-scale data over the cloud leads to the media service being incapable of providing users with high efficient processing assurance; the other aspect is that the location-independent characteristic of cloud computing leads to being incapable of meeting the processing requirement based on a location.
In an actual network, one the one hand, since cloud computing resources are usually centrally deployed in a regional way by a cloud computing service supplier, it is difficult for a user to specify a specific service node and service location, and there is a long time for transmitting data between a centrally deployed cloud server and an actual user; on the other hand, there are a substantial amount of edge serving devices and scattered network resources are unused and not applied in a reasonable way. However, these resources are not only close to users but also have a certain processing ability, there is a problem needed to be solved that how to manage and utilize reasonably service resources at edge of network.